Library "MovingAverages" Contains utilities for generating moving average values including getting a moving average by name and a function for generating a Volume-Adjusted WMA. sma(_D, _len) Simple Moving Avereage Parameters: _D : The series to measure from. _len : The number of bars to measure with. ema(_D, _len) Exponential Moving...
A Simple Crypto Dashboard/Screener which indicates the Price and percentage changes for the Given Period of time i.e for 1 Hr ,4 Hrs, 1 Day, 3 Days, 3 Weeks and 3 - 12 Months. By Default it displays #BTC and its Dominance and current trading pair Price and % changes.
Library "eStrategy" Library contains methods which can help build custom strategy for continuous investment plans and also compare it with systematic buy and hold. sip(startYear, initialDeposit, depositFrequency, recurringDeposit, buyPrice) Depicts systematic buy and hold over period of time Parameters: startYear : Year on which SIP is started ...
Library "FunctionCosineSimilarity" Cosine Similarity method. function(sample_a, sample_b) Measure the similarity of 2 vectors. Parameters: sample_a : float array, values. sample_b : float array, values. Returns: float. diss(cosim) Dissimilarity helper function. Parameters: cosim : float, cosine similarity value (0 > 1) Returns: float
Library "WIPNNetwork" this is a work in progress (WIP) and prone to have some errors, so use at your own risk... let me know if you find any issues.. Method for a generalized Neural Network. network(x) Generalized Neural Network Method. Parameters: x : TODO: add parameter x description here Returns: TODO: add what function returns
Library "FunctionPatternDecomposition" Methods for decomposing price into common grid/matrix patterns. series_to_array(source, length) Helper for converting series to array. Parameters: source : float, data series. length : int, size. Returns: float array. smooth_data_2d(data, rate) Smooth data sample into 2d points. Parameters: data...
Library "FunctionBlackScholes" Some methods for the Black Scholes Options Model, which demonstrates several approaches to the valuation of a European call. // reference: // people.math.sc.edu // people.math.sc.edu asset_path(s0, mu, sigma, t1, n) Simulates the behavior of an asset price over time. Parameters: s0 : float, asset price at...
Library "FunctionMinkowskiDistance" Method for Minkowski Distance, The Minkowski distance or Minkowski metric is a metric in a normed vector space which can be considered as a generalization of both the Euclidean distance and the Manhattan distance. It is named after the German mathematician Hermann Minkowski. reference: en.wikipedia.org double(point_ax,...
Library "regress" produces the slope (beta), y-intercept (alpha) and coefficient of determination for a linear regression regress(x, y, len) regress: computes alpha, beta, and r^2 for a linear regression of y on x Parameters: x : the explaining (independent) variable y : the dependent variable len : use the most recent "len" values of x and...
Library "FunctionNNLayer" Generalized Neural Network Layer method. function(inputs, weights, n_nodes, activation_function, bias, alpha, scale) Generalized Layer. Parameters: inputs : float array, input values. weights : float array, weight values. n_nodes : int, number of nodes in layer. activation_function : string, default='sigmoid',...
Library "FunctionNNPerceptron" Perceptron Function for Neural networks. function(inputs, weights, bias, activation_function, alpha, scale) generalized perceptron node for Neural Networks. Parameters: inputs : float array, the inputs of the perceptron. weights : float array, the weights for inputs. bias : float, default=1.0, the default bias...
Library "MLLossFunctions" Methods for Loss functions. mse(expects, predicts) Mean Squared Error (MSE) " MSE = 1/N * sum ((y - y')^2) ". Parameters: expects : float array, expected values. predicts : float array, prediction values. Returns: float binary_cross_entropy(expects, predicts) Binary Cross-Entropy Loss (log). Parameters: ...
Library "FunctionPeakDetection" Method used for peak detection, similar to MATLAB peakdet method function(sample_x, sample_y, delta) Method for detecting peaks. Parameters: sample_x : float array, sample with indices. sample_y : float array, sample with data. delta : float, positive threshold value for detecting a peak. Returns: tuple with...
Library "Moments" Based on Moments (Mean,Variance,Skewness,Kurtosis) . Rewritten for Pinescript v5. logReturns(src) Calculates log returns of a series (e.g log percentage change) Parameters: src : Source to use for the returns calculation (e.g. close). Returns: Log percentage returns of a series mean(src, length) Calculates the mean of a...
Library "cache" A simple cache library to store key value pairs. Fed up of injecting and returning so many values all the time? Want to separate your code and keep it clean? Need to make an expensive calculation and use the results in numerous places? Want to throttle calculations or persist random values across bars or ticks? Then you've come to...
Library "FunctionProbabilityDistributionSampling" Methods for probability distribution sampling selection. sample(probabilities) Computes a random selected index from a probability distribution. Parameters: probabilities : float array, probabilities of sample. Returns: int.
Library "FunctionElementsInArray" Methods to count number of elements in arrays count_float(sample, value) Counts the number of elements equal to provided value in array. Parameters: sample : float array, sample data to process. value : float value to check for equality. Returns: int. count_int(sample, value) Counts the number of elements...
Library "LinearRegressionLibrary" contains functions for fitting a regression line to the time series by means of different models, as well as functions for estimating the accuracy of the fit. Linear regression algorithms: RepeatedMedian(y, n, lastBar) applies repeated median regression (robust linear regression algorithm) to the input time series...